Deep Reinforcement Learning for Distributed Uncoordinated Cognitive Radios Resource Allocation. - Ankita Tondwalkar; Andres Kwasinski (CoRR, 2019)

Queue-aware QoE-based Rate and Power Adaptation Over Underlay Cognitive Radio Networks: Cross-Layer Design. - Fatemeh Shah-Mohammadi; Ankita Tondwalkar; Andres Kwasinski (WTS, 2020)

Deep Reinforcement Learning for Distributed and Uncoordinated Cognitive Radios Resource Allocation. - Ankita Tondwalkar; Andres Kwasinski (CoRR, 2022)

ECO6G: Energy and Cost Analysis for Network Slicing Deployment in Beyond 5G Networks. - Anurag Thantharate; Ankita Tondwalkar; Cory C. Beard; Andres Kwasinski (Sensors, 2022)

Mulation Analysis of a Reinforcement-Learning-Based Warehouse Dispatching Method Considering due Date and Travel Distance. - Sriparvathi Shaji Bhattathiri; Michael E. Kuhl; Ankita Tondwalkar; Andres Kwasinski (WSC, 2023)

Provisioning Quality of Experience in 6G Networks. - Ankita Tondwalkar; Pilar Andres-Maldonado; Devaki Chandramouli; Rainer Liebhart; Fernando Sanchez Moya; Troels E. Kolding; Pablo Pérez 001 (IEEE Access, 2024)

Proximal Policy Optimization in Uncoordinated and Distributed Multi-Agent Resource Allocation in Cognitive Radio Network. - Ankita Tondwalkar; Andres Kwasinski (WiOpt, 2025)

A Deep Q-Learning Algorithm With Guaranteed Convergence for Distributed and Uncoordinated Operation of Cognitive Radios. - Ankita Tondwalkar; Andres Kwasinski (IEEE Access, 2025)